We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
Numerous studies have shown that datacenter computers rarely operate at full utilization, leading to a number of proposals for creating servers that are energy proportional with r...
Dennis Abts, Michael R. Marty, Philip M. Wells, Pe...
We describe how we have parallelized Python, an interpreted object oriented scripting language, and used it to build an extensible message-passing molecular dynamics application f...
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
This paper describes a novel application for Aspect-Oriented Programming (AOP). By combining the concepts of Business Process Management and AOP, we present an approach for enabli...